Commodityrealreturn Strategy Fund Market Value
PCRCX Fund | USD 11.16 0.06 0.53% |
Symbol | Commodityrealreturn |
Commodityrealreturn 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Commodityrealreturn's mutual fund what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Commodityrealreturn.
03/19/2024 |
| 04/18/2024 |
If you would invest 0.00 in Commodityrealreturn on March 19, 2024 and sell it all today you would earn a total of 0.00 from holding Commodityrealreturn Strategy Fund or generate 0.0% return on investment in Commodityrealreturn over 30 days. Commodityrealreturn is related to or competes with Simt Real, Nexpoint Real, Aamphocas Real, Multi-manager Global, and Short Real. The fund seeks to achieve its investment objective by investing under normal circumstances in commodity-linked derivativ... More
Commodityrealreturn Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Commodityrealreturn's mutual fund current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Commodityrealreturn Strategy Fund upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 0.5834 | |||
Information Ratio | 0.1429 | |||
Maximum Drawdown | 7.61 | |||
Value At Risk | (0.76) | |||
Potential Upside | 1.11 |
Commodityrealreturn Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Commodityrealreturn's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Commodityrealreturn's standard deviation. In reality, there are many statistical measures that can use Commodityrealreturn historical prices to predict the future Commodityrealreturn's volatility.Risk Adjusted Performance | 0.1302 | |||
Jensen Alpha | 0.175 | |||
Total Risk Alpha | 0.1128 | |||
Sortino Ratio | 0.2331 | |||
Treynor Ratio | 1.27 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Commodityrealreturn's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Commodityrealreturn Backtested Returns
We consider Commodityrealreturn very steady. Commodityrealreturn secures Sharpe Ratio (or Efficiency) of 0.2, which signifies that the fund had a 0.2% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Commodityrealreturn Strategy Fund, which you can use to evaluate the volatility of the entity. Please confirm Commodityrealreturn's Downside Deviation of 0.5834, risk adjusted performance of 0.1302, and Mean Deviation of 0.5438 to double-check if the risk estimate we provide is consistent with the expected return of 0.19%. The fund shows a Beta (market volatility) of 0.14, which signifies not very significant fluctuations relative to the market. As returns on the market increase, Commodityrealreturn's returns are expected to increase less than the market. However, during the bear market, the loss of holding Commodityrealreturn is expected to be smaller as well.
Auto-correlation | -0.34 |
Poor reverse predictability
Commodityrealreturn Strategy Fund has poor reverse predictability. Overlapping area represents the amount of predictability between Commodityrealreturn time series from 19th of March 2024 to 3rd of April 2024 and 3rd of April 2024 to 18th of April 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Commodityrealreturn price movement. The serial correlation of -0.34 indicates that nearly 34.0% of current Commodityrealreturn price fluctuation can be explain by its past prices.
Correlation Coefficient | -0.34 | |
Spearman Rank Test | -0.28 | |
Residual Average | 0.0 | |
Price Variance | 0.0 |
Commodityrealreturn lagged returns against current returns
Autocorrelation, which is Commodityrealreturn mutual fund's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Commodityrealreturn's mutual fund expected returns. We can calculate the autocorrelation of Commodityrealreturn returns to help us make a trade decision. For example, suppose you find that Commodityrealreturn has exhibited high autocorrelation historically, and you observe that the mutual fund is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
Timeline |
Commodityrealreturn regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Commodityrealreturn mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Commodityrealreturn mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Commodityrealreturn mutual fund over time.
Current vs Lagged Prices |
Timeline |
Commodityrealreturn Lagged Returns
When evaluating Commodityrealreturn's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Commodityrealreturn mutual fund have on its future price. Commodityrealreturn autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Commodityrealreturn autocorrelation shows the relationship between Commodityrealreturn mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Commodityrealreturn Strategy Fund.
Regressed Prices |
Timeline |
Becoming a Better Investor with Macroaxis
Macroaxis puts the power of mathematics on your side. We analyze your portfolios and positions such as Commodityrealreturn using complex mathematical models and algorithms, but make them easy to understand. There is no real person involved in your portfolio analysis. We perform a number of calculations to compute absolute and relative portfolio volatility, correlation between your assets, value at risk, expected return as well as over 100 different fundamental and technical indicators.Build Optimal Portfolios
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Check out Commodityrealreturn Correlation, Commodityrealreturn Volatility and Commodityrealreturn Alpha and Beta module to complement your research on Commodityrealreturn. Note that the Commodityrealreturn information on this page should be used as a complementary analysis to other Commodityrealreturn's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the FinTech Suite module to use AI to screen and filter profitable investment opportunities.
Commodityrealreturn technical mutual fund analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, fund market cycles, or different charting patterns.